Network Planning Optimization for Resource Allocation
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Solution Overview
Problem
Current network planning techniques often result in underutilized or overutilized resources due to fixed scheduling methods, leading to inefficiencies and failure to identify or leverage available resources effectively, especially in fluid network environments.
Innovation Solution
An integrated method and system for rapid, efficient allocation of resources via a network plan that optimizes equipment and item transmissions, using optimization modeling to generate a dynamic network plan that schedules transmissions, determines resource needs, and routes items to align demand with capacity, without relying on a fixed scheduling framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed schedule is used for network planning, then the scheduling process is simplified, but resource utilization becomes inefficient leading to underutilized or overutilized resources
Solution Approach 1:
The patent transitions from static fixed scheduling to dynamic optimization modeling where the network plan is generated based on current resource availability and demand conditions. The system continuously adjusts resource allocation rather than adhering to predetermined schedules, enabling adaptive response to changing network conditions while maintaining operational simplicity through automated optimization.
Solution Approach 2:
The optimization model dynamically adjusts scheduling parameters such as resource allocation, transmission times, and equipment positioning based on real-time network conditions. By changing these parameters iteratively to optimize the objective function, the system achieves efficient resource utilization without manual scheduling complexity.
2Ease of manufacture
If resources are allocated based on fixed schedules, then planning is straightforward, but available resources for maintenance and optimization are not identified or leveraged
Solution Approach 1:
The optimization model incorporates feedback loops where the generated network plan is evaluated against resource availability and performance metrics. This feedback mechanism identifies underutilized resources and maintenance opportunities that were invisible in fixed scheduling approaches, enabling continuous improvement while maintaining planning simplicity through automated evaluation.
Solution Approach 2:
The system performs self-optimization by automatically identifying and leveraging available resources for maintenance and improvement. The optimization model autonomously determines which resources can be taken offline for maintenance without impacting network performance, eliminating the need for separate resource identification processes.
3Stability of the object's composition
If traditional network planning methods are used, then existing processes are maintained, but computational and memory inefficiencies occur
Solution Approach 1:
The patent replaces traditional mechanical network planning processes with computational optimization modeling. By substituting manual or rule-based planning methods with mathematical optimization algorithms, the system achieves superior computational efficiency while maintaining the stability and reliability of established network planning outcomes.
Data Source
AI summary
Features related to systems and methods for network planning based on optimization modeling of equipment and item transmissions. The network planning may include a model to plan for transmission of items over a network to maximize overall efficiencies over alternative transmission modes. The model may produce a network plan that schedules transmissions, determines the number and types of equipment needed to support the transmissions, assigns equipment to specific locations, and optimally routes items throughout the network.